Senior Machine Learning Operations Engineer
Description For Senior Machine Learning Operations Engineer
SciTec is seeking an experienced Machine Learning Operations (MLOps) Engineer to join and shape their new MLOps team, focusing on Defense, Intelligence, & Space Solutions. This senior role involves deploying and optimizing machine learning models for high-availability systems in both unclassified and classified environments. The position offers a unique opportunity to evangelize MLOps practices and contribute to developing an on-premises development platform for mission-critical applications.
The role requires extensive expertise in Python, Kubernetes, and various MLOps tools, with responsibilities ranging from deploying ML models to implementing advanced deployment strategies and mentoring junior team members. The ideal candidate will have 8+ years of experience leading large-scale ML deployments and strong skills in distributed systems and infrastructure management.
SciTec offers an attractive compensation package ranging from $141,000 to $168,000 annually, along with comprehensive benefits including ESOP, 401(k) with company contribution, full medical coverage, and various insurance options. The position is based in Boulder, Colorado, offering a chance to work with cutting-edge technology in the defense and space sector while maintaining work-life balance through flexible hours and generous PTO.
This role presents an excellent opportunity for a senior engineer looking to make a significant impact in a growing team, working on mission-critical applications while enjoying the benefits of a company that values both technical excellence and employee well-being. The position combines technical leadership, hands-on development, and the chance to shape MLOps practices in classified environments.
Responsibilities For Senior Machine Learning Operations Engineer
- Deploy and maintain high-performing ML models in real-time environments
- Monitor deployed models for drift and implement automated retraining pipelines
- Implement advanced deployment strategies
- Develop modular and flexible ML pipelines
- Build and manage scalable infrastructure using Kubernetes, Docker, Terraform
- Design and implement on-premises development platform using Kubeflow
- Set up monitoring, logging, and alerting systems
- Optimize performance metrics while ensuring fault tolerance
- Work with cross-functional teams to integrate and enhance ML systems
- Define touchpoints with DevOps and Data Engineering
- Mentor junior team members
Requirements For Senior Machine Learning Operations Engineer
- 8+ years experience leading large-scale ML model deployments
- Expertise in architecting Python applications for large-scale systems
- Proven leadership in designing enterprise-grade CI/CD systems
- Advanced expertise in designing distributed pipelines with Protobufs and ZeroMQ
- Advanced expertise in designing workflows using MLflow or Kubeflow
- Expertise in architecting complex Kubernetes and Terraform configurations
- Bachelor's, Master's, or PhD in Computer Science, Engineering, or related field
- Strong problem-solving and analytical skills
- Excellent communication and collaboration capabilities
Benefits For Senior Machine Learning Operations Engineer
- Employee Stock Ownership Plan (ESOP)
- 3% Fully Vested Company 401K Contribution
- 100% company paid HSA Medical insurance
- 80% company paid Dental insurance
- 100% company paid Vision insurance
- 100% company paid Life insurance
- 100% company paid Long-term Disability insurance
- Short-term Disability insurance
- Annual Profit-Sharing Plan
- Discretionary Performance Bonus
- Paid Parental Leave
- Generous Paid Time Off
- Flexible Work Hours
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